Well-being effect of international migration and remittance on human and gender development in South Asian countries

This study investigates the well-being effect of international migration and remittance on human and gender development in selected South Asian countries. The study has adopted panel regression analysis using secondary data from the World Development Indicators and United Nations Development Programme. This database contains information on seven South Asian countries from 1995 to 2020. The study simultaneously applied the Levin-Lin-Chu, Breitung and IM-Pesaran unit root tests to check the stationarity of data. After satisfying the condition, econometric models such as Fixed and Random Effects were executed. Pesaran’s test of cross-sectional independence, the Westerlund test for cointegration and VIF tests were performed in order to check the robustness of the results. As a post-diagnostic tool, the Hausman test suggests that the Fixed Effect models are appropriate for each estimation. The results demonstrate that personal remittance positively and significantly affects human and gender development. Similarly, international migration significantly influences human development while negatively affecting gender development. The study suggests that these countries should prioritize attaining higher remittances by sending more international migrants. Similarly, the provision of cheaper formal channels for remitting money and giving incentives can be effective for higher remittance inflow. Moreover, negotiation at the government-to-government level can effectively expand the international labour market of the selected countries.


Introduction
The new economics of labour migration (NELM) theory argues that households choose migration as a household income diversification strategy.Remittance enriches a household's capacity to invest more in human capital formation [1,2].In contrast, individual-level migration theories, argue that migration decisions and actions are determined by the individual, not the household [3].Irrespective of decisions and actions, does international migration or remittance contribute to human development?Or can migration or remittance inflow influence a nation's or household's well-being?These cutting-edge agendas are still under research and debatable.In the literature, well-being is viewed from two different angles subjective and objective.In general migration researchers define subjective well-being as the quality of life, life satisfaction, and health; meanwhile, objective well-being is mostly through income and investment aspects [4][5][6].The well-being effects of migration are almost similar at household and country levels.
Migration contributes to developing discourses through multidimensional socioeconomic issues [7].The literature argues that remittance inflow enables households and migrant-sending countries to invest in development purposes.For instance, education, health and other socioeconomic infrastructures may contribute to higher human development within a country [8].Remittance is the outcome of international migration, which acts as a tangible input for the overall development of migrant-sending countries [3,[9][10][11].In the literature, both long-term and short-term effects of migration and remittance have been observed from the perspectives of human development and gender development [12][13][14].It has been seen from the perspective of different countries and contexts that migration and remittance have mostly positive and significant effects in terms of improving human development index (HDI) score [15][16][17][18][19].
The question is: if migration or remittance positively influences development indicators such as HDI, then to what extent and direction are migration and remittance related to the Gender Development Index (GDI)?In the literature, a mixed outcome is reflected.It is argued that migration and remittance increase disparities; however, in the long run, the effect varies based on the type and pattern of migration history.The effect is more rigorous on poorer communities than on economically well-off communities [20].This argument suggests that the direction and extent of the impact of migration or remittance on well-being differ based on economic strata, perspective, and migration history.A connection has also been found between migration/remittance and gender development.In terms of achieving sustainable gender development, migration is considered an effective instrument, however, migration action is primarily concentrated on men [21].Meanwhile, migration contributes to transforming gender roles in the home country [22].Similarly, remittance-receiving status works as an intrinsic development mantra in the home country for issues such as the alleviation of poverty, and changing gender roles [23].Moreover, migrant women encounter risks and shocks, which triggers them to send more remittances for self-insurance against vulnerabilities [24].Migration enables women to enjoy freedom of mobility, become involved in economic activities, and make decisions regarding household well-being, which contributes to the gender development of their country [25].
Though literature is available from developing and sab-Saharan African (SSA) countries' perspectives, little evidence has been found relating to development indicators such as HDI, GDI and gender inequality in the South Asian context.Moreover, the above indicators represent a country's well-being scenario, viewed through the migration and remittance lens.Furthermore, as relatively recent indicators, gender inequality and gender development have attracted much interest.Against this backdrop, the novelty of this study is its examination of the welfare effects of remittance and migration on human and gender development from the perspective of South Asian countries.The study aims to investigate whether there is any effect of migration/remittance on human and gender development in the context of South Asian countries.
In the successive stage of this manuscript, the study focuses on the literature review with the conceptual framework, materials and methods, results and discussion and finally, concussion and policy recommendations.The materials and methods section provides a glimpse of materials used for data extraction and analysis.The policy recommendations are provided based on the results of the study.
The minimal dataset used for analysis is uploaded by the corresponding author titled 'Replication Data for: International migration and remittance in south Asian countries', Harvard Dataverse.The dataset is available at the link: https://doi.org/10.7910/DVN/IYWFKB.

Literature review
Numerous studies have explored the connection between migration and human development from different countries' contexts and perspectives.The nexus between remittance and human development has been investigated at the household level and across countries, including sub-Saharan African (SSA) countries, South Asian countries, and other developing and lowincome countries [13,[16][17][18][19][25][26][27].For analysis, different types of data such as panel, timeseries and cross-sectional have been applied in order to examine the effects of remittance and migration on human development; in most cases, the HDI has been used as a proxy for representing human development [13, 16-19, 25, 27-31].However, the debate continues from different perspectives as the dimensions and definitions of human development vary significantly.The literature argues that migration and remittance have significant positive long-term effects.Interestingly, remittance contributes positively to human development [18,19,29,32,33].In Sri Lanka, remittance is a significant predictor of human capital formation.However, the development effect varies based on the government's approach to migrants, which indicates that institutions and governmental policy are closely intertwined with remittance inflow [32,34].A positive association exists between human development and remittance: the composite index combined with long healthy life, knowledge accessibility and a decent living standard [35].Similarly, the literature argues that a strong connection exists between migration/ remittance and inequality.
The evidence suggests that in South Asia, remittance significantly and positively influences economic growth [36][37][38].However, at the household level, worker remittance has a longterm yet minor impact on income inequality [39,40].Conversely, a positive relationship between remittance and income inequality at the household level is also evident in the literature.Similarly, the relationship between asset accumulation and income distribution is well described by an inverted U-shaped curve, indicating that effects differ in the short and long term [41,42].However, this finding is opposed by Tokhirov et al. [43], who discovered a Ushaped relationship between remittance and income inequality.At the early stage of migration, a community faces higher inequality; however, this declines when migration is a long-term trend.In poorer communities, remittance increases inequality, whereas the reverse effect is observed in more affluent communities [2,26,44,45].
The effects of migration and remittance have sustainable and long-lasting impacts on gender; hence, comprehensive indicators instead of a single indicator should be adopted for analysis [12].GDI is therefore a frequently used indicator in the literature.The GDI is included as one of the well-being measures however, it needs to be more focused than the HDI.This indicator is often misinterpreted in the literature [13,14,46].GDI exemplifies women's overall gender well-being and relative health status.It is also argued that compared to other development indicators, GDI is socio-economically a powerful and overarching indicator [47,48].Evidence suggests that in economic growth, remittance and GDI have a significant and positive influence [39,49].Nevertheless, more research is required in order to understand the dynamic and complex association between migration, remittance and gender development.
After a rigorous literature review, the study found that limited literature is available from different countries and contexts, such as SSA and East Europe.However, literature from the South Asian context is rarely available.Moreover, GDI and HDI are seldom explored with connection to migration and/or remittances.The South Asian countries, especially Bangladesh, India and Pakistan, send a bulk of human resources as labourers to different destinations each year.Therefore, the nexus between migration or remittances with human development and gender development grabs the researcher's attention more.In this context, this study gains interest to investigate the effects of remittance on gender and human development.

Conceptual understanding
Migration decision and remittance earning are influenced by a set of micro and also macro economic development indicators where context or circumstances has a predominant role (Fig 1).The literature argues that there is a strong connection between migration/remittance and human development, where the households choose migration as a livelihood diversification strategy.
Similarly, as a outcome of migration, economic and social remittances contributes to uplifting economic growth as well as human and gender development.In this connection, the study aims to explore whether there is any significant influence of migration and remittance on gender and human development in South Asian countries' context.

Data
This study adopted panel data in order to estimate the effects of remittance and migration on development indicators.For analysis, the required data were extracted from two database sources: the World Bank (WB) and the United Nations Development Program (UNDP).From these online database sources, data were retrieved between August 25 and 30, 2022.The study focused on seven South Asian countries (Bangladesh, India, Pakistan, Sri Lanka, Maldives, Pakistan and Nepal), while the dataset included a time frame from 1995 to 2020.Bhutan and Afghanistan were removed from the original list of countries because most of the required data for these two countries were missing.Among the variables, personal remittance (in current US$), personal remittance received (% of GDP), international migration stock, and Gini index data were retrieved from World Development Indicators (WDI) [48,49].At the same time, data on HDI, GDI, and Gender Inequality Index (GII) were extracted from the UNDP [35].Data on personal remittance were available for each of the corresponding years.However, international migration stock was calculated accounting for a five-year interval.Similarly, the countries under study started calculating GDI and GII systematically in 2008; prior to that, the calculation did not follow any systematic pattern.This study used the HDI score as a proxy for human development.The GDI value was considered a proxy for gender development, while the GII value represented gender inequality.This forecasting method balanced the database, i.e., filled up the missing values.

Dependent variables
Human development.A higher index value indicates that a country has moved forward to better health and education levels with higher national income [35].The components of HDI are: i. a long, healthy life (measured by life expectancy at birth) ii.access to knowledge (average and expected schooling years) iii. decent living standard (measured by per capita Gross National Income)

Gender development
Using three fundamental dimensions of human development, the GDI indicates the achievement gaps between women and men [35].A higher GDI value indicates a better standard of gender development which is expected to be positively linked with remittance.The indicators of GDI are: i. life expectancy at birth ii.knowledge (expected and mean schooling years) iii. standard of living (GNI per capita) (listed in Table 1) Stationarity test.Before regression analysis, unit root tests including Levin-Lin-Chu (LLC) and Breitung unit root tests were performed in order to check whether the series was stationary.In panel estimation, the variables are required to be stationary [52].Hence, this study used both tests in order to examine whether the variables were stationary at level or at least at first difference.In addition, the IM-Pesaran-Shin test is executed to examine the stationarity of the panels.
Levin-Lin-Chu unit root test.For a balanced dataset, the Levin-Lin-Chu unit root test assumes: Null Hypothesis : H 0 : p i ¼ 0 i !every time series contains unit roots Alternative Hypothesis : H A : p 0 ¼ p 0i !every time series is stationary Following other unit tests, the LLC also assumes the independence of each cross-section process.The estimated equation below serves as the main foundation for the LLC test.
Breitung unit root test.The Breitung unit root test is different from the LLC unit root test.The LLC unit root test depends on t statistics of regression analysis which are later revised.The t-statistics must be non-zero as it considers panel-specific averages and trends.In perfectly balanced data (a pre-requisite), the Breitung unit root test applies the data-altering technique as an alternative strategy for attaining a t-statistic.The t-statistic will be asymptotically generally distributed if T ! 1 and N ! 1.Each of the panels will provide an autoregressive parameter.Likewise, the Levin-Lin-Chu unit root test and the Breitung unit root test also assume: Null hypothesis : H 0 : Every series contains unit roots Alternative hypothesis : H A : Every series is stationary The Breitung unit root test best fits when all the panels have the same autoregressive values; however, it is also applicable when heterogeneity exists due to the panel's parameters.This test has been found to be more powerful and effective for a small number of observations [53,54].
IM-Pesaran-Shin test.The IM-Pesaran-Shin test estimates a t-test in order to examine unit roots in heterogenous panels, it assumes in null hypothesis that all panels are not stationary.
Null hypothesis : H 0 : All panels contain unit roots Alternative hypothesis : H 0 : Some panels are stationary Empirical, analytical tools.Panel data considers temporal and spatial dimensions, the spatial dimension covers cross-sectional units and the temporal dimension covers periodic observations [55].This study used panel regression analysis with a panel dataset of seven countries over the period 1995-2020.The xtreg command is executed in STATA 17 in regression analysis.
The general formula for panel regression analysis is explained in Eq 2.
Where α and b are coefficients; y indicates dependent variables, x indicates explanatory variables; i indicates the number of individuals or cross sections, and t represents the number of periods.Executing the Fixed Effects (FE) and Random Effects (FE) models is necessary for the panel regression analysis.Following the execution of those models, a diagnostic test is required in order to examine whether the FE or RE model is most appropriate for estimation [56].
Fixed Effect (FE) model.The FE model is significantly distinguished from the common and random effect models; nevertheless, it also adopts the basic principles of Ordinary Least Square (OLS) estimates.In FE models, the assumption is that the differences between crosssections or individuals can be represented using different intercepts.FE models are more reliable than RE models.The Fixed Effect Panel regression equation is provided in Eq (3).
Where variables represent the number of cross-sections, i.e., the number of periods, the FE model allows a random variable (individual-specific effect) to be correlated with independent variables [56,57].
Random Effect (RE) model.If the inference variables are likely to be correlated between individuals and periods, then the RE model is generally applied.This model adjusts the difference between intercepts by incorporating error terms.The RE model is more effective in eliminating heteroscedasticity than other models.Hence, this model is also called the Error Component Model (ECM) or Generalized Least Square (GLS) Technique.The FE model holds the basic principles of OLS, in contrast to the RE model.This model contains the principles of GLS or maximum likelihood.The model assumes differences between intercepts for each cross-section or individual; hence, two residual terms exist simultaneously in the equation.Intercept term 1 is a combination of time series and cross-section; intercept term 2 is an individual residual, which is random by nature [56].The general equation of a RE model is illustrated in Eq 4. Pesaran's CD test of cross-sectional independence.The Pesaran test assumes no cross-sectional dependence under the null hypothesis.Hence, rejection of the null hypothesis will mean that there exists cross-sectional independence.

Westerlund cointegration test
The Westerlund cointegration test is performed in order to examine whether the panels are cointegrated.

Null hypothesis : H 0 ¼ No cointegration
Alternative hypothesis : H A ¼ Some panels are cointegrated

Ethical consideration
This study is conducted using secondary sources of data.Hence, no face-to-face interaction was required.Therefore, no sensitive questions were asked or dealt with at any stage of producing the paper.

Results of the stationarity test
Before regression analysis, this study examined whether the data was stationary, using LLC and Breitung unit root tests.The results (Table 2) from both the tests showed that, personal remittance, personal remittance received (% of GDP), international migration stock, human development, and gender development were significant (1% level) at the first difference.The results also showed that there were no unit roots in the mentioned panels.In contrast, gender inequality did not satisfy the criteria of the LLC test.However, there were significant results when the first difference is considered.While performing the second generation IM-Pesaran-Shin test, the variables were found to be stationary at second difference.

Effects of remittance and migration on human development
The Hausman identification test (1978) (Table 3) indicates that the FE model is appropriate for analysing the effects of remittance and migration on human development.The FE panel regression analysis results (Table 3) demonstrate that personal remittance has a significant and positive (at a 1% level) effect on human development.A 1% improvement in remittance leads to a positive change in the human development score by 0.00037; this result was expected.Similarly, international migration stock positively affects the HDI score.The results show that if the stock of international migration increases by 1%, the human development score tends to increase by 0.012 points.In addition, one of the vital determinants of human development was found to be negatively connected with gender inequality.It can be seen that if gender inequality increases in terms of achievements (adolescent birth and maternal mortality ratio, labour market participation, and empowerment, i.e., shares in parliament seats, minimum secondary education for each gender), it leads to a decrease in human development score.Conversely, if the gender inequality index increases by 1%, it decreases the human development score by 0.16, which was also expected.The results of Pesaran's test of cross-sectional independence (Table 3) suggest accepting the null hypothesis thus there exists no cross-sectional dependency among the panels.The Westerlund test for checking cointegration also suggests that there exists no cointegration among the panels.

Remittance and migration-gender development lens
For this model, the Hausman specification test suggests the FE model is appropriate (Table 4).
If remittance increases by 1%, then the GDI score also increases by 0.00019 points (significant at a 1% level), and the sign and direction are as expected.The results also portray that if international migration increases by 1%, the GDI score tends to decline by 0.004 points.As expected, a 1 unit increase in the HDI score leads to an improvement in gender development by 0.2 points (significant at a 1% level).The result suggests that if the overall HDI score increases, the gap between women and men reduces.Moreover, the GII is inversely related to the GDI i.e., if the GII value rises by 1 point, the GDI declines by 0.119 points.GII demonstrates a reduction in HDI based on differences in achievements between women and men in terms of reproductive health, labour market participation, and empowerment.The Pesaran's test of cross-sectional independence demonstrates that the cross-section panels are independent, while the Westerlund test for cointegration suggests that the panels are not-cointegrated.

Remittance, migration and human development
This study found that remittance positively and significantly contributes to the human development score with the expected sign and direction.This finding is consistent with the existing literature [19,28,34].Workers' international remittance positively affects human development in the long run.Hence, remittance acts as the backbone of many developing and sab-Saharan African countries [27,29,31].The HDI indicates the overall quality of life of a country's people, which is significantly and positively enhanced by the remittance inflow [27].It can be understood that with a higher remittance inflow, the economy also benefits; this is because, with the heightened remittance, country's capability to invest in development sectors increase.This investment in direct productive and human development sectors, such as health and education, results in a positive move towards human development.With higher investment of remitted money, the country can move forward to attain a longer life expectancy.Similarly, this investment enables countries to achieve higher average years of schooling.These two indicators of human development directly improve a country's human capital formation, which will help to safeguard future national income through better livelihood opportunities [58].Remittance also helps to achieve a decent standard of living by increasing per capita Gross National Income (GNI).This finding was also expected because Bangladeshi migrants' income is added to the national accounts.Moreover, the remitted money is primarily invested in productive activities, which may raise national income.
Likewise, international migration stock also positively affects HDI score.However, this finding contradicts the findings of Akanbi [30], who reported a negative effect of migration on human development in the African context.Likewise, Sanderson and Kentor [30] also reported a negative effect of migration on human development from developing countries' perspectives.Migration brings not just economic remittances but also social remittances, such as attitude, knowledge, beliefs, practices etc. [30].This may indirectly influence socioeconomic and cultural development, leading to higher human development scores.Migration is not only essential for earning foreign currency but also contributes to socioeconomic and cultural transformation.
The study also found that human development is associated with lower gender inequality.Lowering inequality between women and men can ensure the sustainable development of a country [35,59].The results allowing women to fall behind men will not lead to positive growth in human development.In South Asian countries, women lag behind in health, labour market participation, and empowerment dimensions.In South Asia, by adopting the quota system, Bangladesh has allotted 13% of it's government seats, Pakistan 17% of seats in its national assembly, and India 8.3% of seats in the lower house to women [60].Through alloting more seats to women in parliaments, increasing access to labour market participation, and providing better health service for women, gender gaps in achievement between women and men can be lessened.

Remittance, migration and gender development
Among different socioeconomic indicators, gender plays a critical role in sustainable development.It is also evident in the agro-climatic zones in Pakistan, where poverty is predominant with other socioeconomic vulnerabilities.Poverty reduction as a development indicator is also influenced by a number of determinants.Increased inflow of FDI also stimulates employment and economic growth [37,[61][62][63][64][65].
In this study, the findings suggest that in the south Asian countries, remittance is positively associated with gender development.This may be because higher remittance can be invested in women's development, such as education and health, which can increase life expectancy at birth.In addition, through remittance, infrastructure for access to education can be attained, which may lead to an increase in expected and average years of schooling.Investment in the productive sector can also heighten national income, including a higher share of women's contribution, which may lead to better living standards [36][37][38].Remittance also improves economic well-being, including better dietary intake and health status for women [66].Moreover, higher educational investments promote women's education [67].The literature argues that remittance nurtures socioeconomic development, such as an increased standard of living and sustainability [67].
Conversely, international migration leads to a decrease in gender development.This may happen because the migration rate of women is significantly lower than that of men in South Asian countries such as Bangladesh [68].In a developing country, generally, men choose migration as a livelihood diversification strategy, while women are left behind to tend to household responsibilities.They are often restricted by other household members from going outside for education or healthcare services.Moreover, remittance expenditure depends on gender, type of family, and household head [69][70][71].Likewise, households in a country may not benefit if the country's migration is male-centric.Mobilizing women towards international migration can be an effective tactic for women's development.Similarly, circumstances such as the location of a household have an effective on international migration belongs.Rural households face socioeconomic and cultural bottlenecks and other obstacles to women's development.Gender development may also depend on good governance, institutional coordination, gender-centric policies, and effective implementation of policies.
In contrast, human development is positively related to gender development.If the overall HDI score increases, the gap between women and men may reduce, which implies that gender development is ensured in terms of achievement in life expectancy, knowledge, and GNI per capita.Conversely, GII demonstrates a reduction in HDI based on differences in achievements between women and men regarding reproductive health, labour market participation, and empowerment.If the adolescent birth rate and maternal mortality ratio increase, if labour force participation declines, if the share of women in parliament declines; and if the minimum population with secondary education declines, GDI will be negatively affected.In other words, if gender inequality decreases, it indicates that gender is developing, i.e., inequality between women and men is decreasing.

Strengths and limitations
This study has some unique strengths; it examines the effects of remittance on human development and gender in the South Asian context, which adds value to the existing literature.In the South Asian context effects of remittance on macroeconomic determinants have been relatively less often explored in the literature.Furthermore, little evidence is found reagrding the nexus between remittance on gender development indicators which is also investigated in this study.This paper has some limitations, such as data scarcity on the stock of international migration.International migration stock data is available at five-year intervals.In addition, data on GDI and GII were not collected systematically for each country and each year.The study focused on seven countries in South Asia belonging to SAARC and covered 26 years of data starting from 1995.Countries such as Afghanistan and Bhutan were removed from the list due to the unavailability of required data.Databases covering more countries and years could provide more robust results.Along with a regional scenario of migration and wellbeing, country-specific analysis can provide a detailed overview of the effects of remittance and migration.

Policy recommendations
The results demonstrate that migration stock and remittance are two significant predictors of human development; hence, policies like extending migration stock towards different lucrative destinations that provide higher wages and job securities should be prioritised.Instead of sending unskilled labourers, the countries should prioritize sending skilled labourers abroad to get higher remittance from the destination countries.In this regard, in collaboration with NGOs, the government may launch different skill development initiatives like training and motivational sessions may be effective.Similarly, to increase remittances through formal channel, incentives to the sending amount may be fruitfull.In addition, the migrant sending countries should explore and extend new labour markets for sustainable development.

Conclusion
The literature argues that a connection exists between migration/remittance and development indicators such as human and gender development.In the literature, the association has been measured from different countries' contexts and perspectives; however, few studies have investigated the connection from the perspective of South Asian countries.The novelty of this study lies in its examination of the effects of migration and remittance on human development and gender development from this perspective.The study found that human development, remittance, and stock of international migration positively and significantly affect human development [36,62,64]; however, gender inequality negatively affects human development.The findings confirm that in human development, both remittance and international migration stock have an influential positive role; hence, interventions should be undertaken to increase remittance earnings through a higher stock of international migrants in order to achieve sustainable development.Likewise, on gender development, remittance influences positively; however, international migrant stock affects it negatively.This result was expected, as there are still different dynamics in gender development due to migration.Inequality reduction, gender development, higher remittance, and migration stock play a crucial role for sustainable human development [38]; therefore, policies for increasing remittance inflow by sending more international migrants can be effective.In the South Asian context, priory should be given to the skills development of the young people through motivational and training sessions.In collaboration with non-government organizations, the government could move forward in this regard.Moreover, incentive provisions for increasing remittance could also be effective.Searching for new labour markets and negotiating with the government could also create better opportunities for international job seekers.Therefore, a higher scope of earning remittance would be opened up.To encourage more international migration, migration-friendly policies such as training for skills development, workshops, and seminars could be arranged in order to stimulate awareness among the younger generation.Finally, host countries should encourage skilled workers to make migration decisions for higher remittance attainment.This migration strategy should not be confined to men; women should also be encouraged to migrate internationally.

Table 1 . Variables with descriptive statistics. Variables Description Source Measurement unit Expected result Observations Mean Standard deviation Min Max Inequality
The Gini index value is used to represent inequality in income.A higher value shows higher inequality and vice versa.https://doi.org/10.1371/journal.pone.0300597.t001 There are several methods for examining the appropriateness of models, for example, the Hausman test, Chow test, and Test Lagrange Multiplier.This study adopted the Hausman test to test the appropriateness between FE and RE models.
[56] hypothesis : H 0 ¼ The random effect is appropriate Alternate hypothesis : H A ¼ The fixed effect is appropriate Results: If p>0.05 = RE is appropriate, whereas if p<0.05 = FE is appropriate[56].